text:
How to get the label and bbox's point from the image_demo.py

Prerequisite

[X] I have searched Issues and Discussions but cannot get the expected help.
[X] I have read the FAQ documentation but cannot get the expected help.
[X] The bug has not been fixed in the latest version (master) or latest version (3.x).

💬 Describe the reimplementation questions
I had run the image_demo.py, and i want to get the label and bbox.
When i print the result, it occur a lot of things:

[array([[ 1.9062561e+02, -2.0416601e+00,  1.9904964e+02,  1.8412046e+01,
         1.1927172e-01],
       [ 1.8427026e+02,  2.3824237e-01,  1.9281366e+02,  1.6635750e+01,
         4.3546416e-02],
       [ 1.7938216e+02, -4.4338244e-01,  1.9873393e+02,  1.7194103e+01,
         1.3683819e-02],
       [ 1.9207216e+02,  6.6276413e-01,  1.9831039e+02,  1.0290908e+01,
         4.2002583e-03],
       [ 1.8946248e+02, -3.4689537e-01,  2.1362819e+02,  1.8071379e+01,
         2.7685580e-03],
       [ 2.0108842e+02,  1.3981505e-01,  2.1234363e+02,  9.5635185e+00,
         2.4734177e-03],
       [ 1.7820163e+02,  1.8772141e+00,  1.8726802e+02,  1.4660118e+01,
         2.4597589e-03],
       [ 1.3057306e+02, -7.9792619e-02,  1.4114674e+02,  9.6142597e+00,
         1.8394142e-03],
       [ 2.2172197e+02,  1.8759282e-01,  2.3508667e+02,  8.5633316e+00,
         1.4005082e-03],
       [ 2.4947389e+02, -1.6969869e-02,  2.5714200e+02,  6.2540216e+00,
         1.0278792e-03],
       [ 2.3690672e+02,  6.3027900e-01,  2.4738524e+02,  6.9039278e+00,
         4.7688204e-04]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([[ 2.4159468e+02,  4.2274961e-01,  2.5396782e+02,  7.5705914e+00,
         2.3141257e-02],
       [ 2.2172197e+02,  1.8759282e-01,  2.3508667e+02,  8.5633316e+00,
         8.2414644e-03],
       [ 2.3690672e+02,  6.3027900e-01,  2.4738524e+02,  6.9039278e+00,
         8.1556989e-03],
       [ 2.4947389e+02, -1.6969869e-02,  2.5714200e+02,  6.2540216e+00,
         4.7696368e-03],
       [ 1.7938216e+02, -4.4338244e-01,  1.9873393e+02,  1.7194103e+01,
         4.7104461e-03],
       [ 2.1915945e+02, -2.3330554e-01,  2.4948927e+02,  1.1226179e+01,
         4.5511140e-03],
       [ 2.0108842e+02,  1.3981505e-01,  2.1234363e+02,  9.5635185e+00,
         3.5560494e-03],
       [ 1.8946248e+02, -3.4689537e-01,  2.1362819e+02,  1.8071379e+01,
         2.8939599e-03],
       [ 1.7820163e+02,  1.8772141e+00,  1.8726802e+02,  1.4660118e+01,
         1.7416875e-03]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([[ 2.4159468e+02,  4.2274961e-01,  2.5396782e+02,  7.5705914e+00,
         1.7043254e-03],
       [ 2.2172197e+02,  1.8759282e-01,  2.3508667e+02,  8.5633316e+00,
         9.1943139e-04],
       [ 2.1915945e+02, -2.3330554e-01,  2.4948927e+02,  1.1226179e+01,
         6.9657335e-04],
       [ 2.4947389e+02, -1.6969869e-02,  2.5714200e+02,  6.2540216e+00,
         4.0267309e-04],
       [ 1.9607605e+02, -9.2385322e-01,  2.1775485e+02,  1.7484865e+01,
         3.3800941e-04]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([[1.9207216e+02, 6.6276413e-01, 1.9831039e+02, 1.0290908e+01,
        3.1496727e-04]], dtype=float32), array([[ 7.0064438e+01,  5.7137424e+01,  2.0781766e+02,  1.6958020e+02,
         9.3431890e-01],
       [ 7.2355164e+01,  4.6862583e+01,  1.7435797e+02,  9.8821281e+01,
         1.0591656e-02],
       [ 1.8946248e+02, -3.4689537e-01,  2.1362819e+02,  1.8071379e+01,
         1.3933333e-03],
       [ 1.7820163e+02,  1.8772141e+00,  1.8726802e+02,  1.4660118e+01,
         9.1950339e-04],
       [ 2.1641862e+02,  2.7605198e-02,  2.4090166e+02,  1.5915675e+01,
         6.1214453e-04]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([[1.9207216e+02, 6.6276413e-01, 1.9831039e+02, 1.0290908e+01,
        4.2585388e-04]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([[1.7820163e+02, 1.8772141e+00, 1.8726802e+02, 1.4660118e+01,
        4.8008375e-04]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([[ 1.3057306e+02, -7.9792619e-02,  1.4114674e+02,  9.6142597e+00,
         2.8988586e-03],
       [ 1.9607605e+02, -9.2385322e-01,  2.1775485e+02,  1.7484865e+01,
         4.4319168e-04]], dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32), array([], shape=(0, 5), dtype=float32)]

I don't know which part is about label and bbox
Environment
The environment is Ok
Expected results
I want to get the label and bbox of the image: bench and the point

Additional information
No response

If you want to get image visualization, the result has been saved in args.out_file.
If you want to get bbox result and label more clearly, you can refer to  https://github.com/open-mmlab/mmdetection/blob/master/mmdet/ models/detectors/base.py#L276


text:
Upgrade to PyTorch 1.0

This PR solves #155. In fact, this repo can support PyTorch 1.0 without any changes. Only some minor changes are needed for mmcv.
We made some minor updates though.

Support half tensors (fp16) for roi_align and roi_pooling.
Remove some legacy code.

You need to use the pytorch-1.0 branch of mmcv with this PR. After the branch being merged, mmcv will be updated to v0.2.2.
The results are shown in the below table.

PyTorch 0.4.1
PyTorch 1.0.0

RPN
57.1
57.0

Faster R-CNN
36.4
36.5

Mask R-CNN
37.3 / 34.2
37.3 / 34.2

RetinaNet
35.6
35.7

Cascade R-CNN
40.3
40.4

Cascade Mask R-CNN
41.3/35.7
41.2/35.7

@hellock How do one install mmcv>=0.2.2 ? The master branch on its github channel installs version 0.2.1

@adityaarun1 mmcv 0.2.2 is not released yet, you can checkout the pytorch-1.0 branch of mmcv to use it.

Hi @wangg12 , recently released v0.2.2 is the version for PyTorch 1.0. If you'd like to use PyTorch 1.0, you can checkout to the pytorch-1.0 branch of mmcv, which may be released later as v0.2.3.

@zxt881108 Currently the speed of PyTorch 1.0 and 0.4.1 is similar since we made only minor changes, we will take time to optimize it.

source: gharchive/pull-request

repo: open-mmlab/mmdetection

license_type: permissive

license_source: github-api


text:
add bbox_overlaps for fp16 to save memory and keep speed

In GPU and CPU environments with limited hardware resources, bbox_overlaps often has CUDA memory allocation errors. To do this, we added bbox_overlaps on FP16 to save memory and keep speed at the same time.

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.liphone seems not to be a GitHub user. You need a GitHub account to be able to sign the CLA. If you have already a GitHub account, please add the email address used for this commit to your account.You have signed the CLA already but the status is still pending? Let us recheck it.

Hi @li-phone ,
Thanks for the PR. This feature is quite interesting and valuable, so we plan to merge it in the next release (end of April). Could you sign the CLA and fix the lint/CI issue? Furthermore, we suggest adding unit tests for the FP16 feature to ensure correctness, thus we do not need to train models to do that.

Hi @li-phone ,
Thanks for the quick response. Do you have some statistics about how much the memory and the time cost are reduced?
If you have that, could you post them in your PR message and add some comments in the code you modified, thus future developers could recognize the value of the modification. We plan to merge this PR for the next release (end of this month)

Hi @li-phone ,
Thanks for the quick response. Do you have some statistics about how much the memory and the time cost are reduced?
If you have that, could you post them in your PR message and add some comments in the code you modified, thus future developers could recognize the value of the modification. We plan to merge this PR for the next release (end of this month)

Yes, we proved it as follows:
Prove:
Assume bboxes1 is M x 4, bboxes2 is N x 4, when mode is 'iou', there are some new generated variable when calculating IOU using bbox_overlaps function:
1) is_aligned is False
area1: M x 1
area2: N x 1
lt: M x N x 2
rb: M x N x 2
wh: M x N x 2
overlap: M x N x 1
union: M x N x 1
ious: M x N x 1
        Total memory:
            S = (9 x N x M + N + M) * 4 Byte

        When using FP16, we can reduce:
            R = (9 x N x M + N + M) * 4 / 2 Byte,
            R large than (N + M) * 4 * 2 **is always true** when N and M >= 1.
            Obviously, N + M <= N * M < 3 * N * M, when N >=2 and M >=2,
                              N + 1 < 3 * N, when N or M is 1.

        Given M = 40 (ground truth), N = 400000 (three anchor boxes
        in per grid, FPN, R-CNNs),
            R = 275 MB (one times)

        A special case (**dense detection**), M = 512 (ground truth),
            R = 3516 MB = 3.43 GB

        When the batch size is B, reduce:
            B x R

        Therefore, **CUDA memory runs out frequently**.

        Experiments on GeForce RTX 2080Ti (11019 MiB):

        |   dtype   |   M   |   N   |   Use    |   Real   |   Ideal   |
        |:----:|:----:|:----:|:----:|:----:|:----:|
        |   FP32   |   512 | 400000 | 8020 MiB |   --   |   --   |
        |   FP16   |   512 | 400000 |   4504 MiB | **3516 MiB** | **3516 MiB** |
        |   FP32   |   40 | 400000 |   1540 MiB |   --   |   --   |
        |   FP16   |   40 | 400000 |   1264 MiB |   **276MiB**   | **275 MiB** |

    2) is_aligned is True
        area1: N x 1
        area2: N x 1
        lt: N x 2
        rb: N x 2
        wh: N x 2
        overlap: N x 1
        union: N x 1
        ious: N x 1

        Total memory:
            S = 11 x N * 4 Byte

        When using FP16, we can reduce:
            R = 11 x N * 4 / 2 Byte

    So do the 'giou' (**large than 'iou'**).

    Time-wise, **FP16 is generally faster than FP32.**

    When gpu_assign_thr is not -1, **it takes more time on cpu
    but not reduce memory.**
    Therefore, **we can reduce half the memory and keep the speed.**

authors: CLAassistant ZwwWayne li-phone


text:
[Feaute]support spconv2.0

Motivation
Support spconv2.0 in mmdet3d dev branch.  If the user installed spconv2.0, the code would use spconv2.0 first. And if spconv2.0 is not installed, the code will use mmcv's spconv op.
BC-breaking (Optional)
.
Checklist

[x] fix get_start docs
[x] fix ut
[x] add spconv check in collect_env.py

@VVsssssk, I have one question after training with the spconv2. If we use the mmdet3d/apis/inference.py for doing inference_detector(model, pcd) than which version will it choose spconV2 or V1? However, I think it's using V1 which is causing a dimensional mismatch with the trained weights!
I will really appreciate if you can confirm this, thanks

authors: VVsssssk ammaryasirnaich


text:
Updated the snn benchmark with torch.compile for Norse

Added torch.compile to Norse
Happy to hear opinions and change as needed :)

I re-ran the tests on a AMD 5965WX and 4090 Nvidia GPU

nice results dude! Given that both Cameron and me had issues running torch.compile on the Norse code, I'm wondering if you changed anything since then? Was it the neuron model that caused the problem you think?

Thanks! We had some old JIT annotations that clashed with the compiler. I added tests for torch.compile with the recent NIR features. https://github.com/norse/norse/commit/22a17ec20fdb7828e1c79c00ddb5a45ee9f4bb7e#diff-d0aebb58ae5562a7d7d3379b7202e4ee76ede47d05abe597a0996828731d6b65L21
But I've been able to compile things locally for a while, so I don't think this explains it. My best hunch currently is that the changes in PyTorch 2.2 improved support for our weird NamedTuple state objects. In any case it seems to be working now :shrug:

authors: Jegp biphasic

license: MIT


text:
update strategie

https://github.com/open-orchestra/open-orchestra-media-admin-bundle/pull/197
https://github.com/open-orchestra/open-orchestra-workflow-function-bundle/pull/94
https://github.com/open-orchestra/open-orchestra-cms-bundle/pull/1556

:+1:

authors: alavieille itkg-nanne

license_source: bigquery


text:
Add initial support for NetBSD

Accept NetBSD as a string in system.py and return a string for the boot options.
Currently, I don't know how to figure out the real cmdline used when booting NetBSD, so in this MR the string is the same as for Windows, ie, nothing.

I will try to figure out how to find the cmdline in NetBSD and update this patch.

Thanks for the patch @db7

I will try to figure out how to find the cmdline in NetBSD and update this patch.

Ok, I'm setting the PR as draft meanwhile.

I've got reply in the mailing list regarding that (see https://mail-index.netbsd.org/netbsd-users/2024/08/15/msg031649.html).
In summary, there is no super easy way hot to do that because there are not many options one passes to the kernel. The kernel name should be sufficient. If we really want to get these options we'd have to write a small C program to perform some sysctl calls. The information gained is very limited, though.
I suggest keeping the PR as it is, ie, with "<boot args fetching is unsupported ...>".

Good for me, thanks for looking. I did a quick check as well, and it does not seem easy indeed.


text:
Feature: Add attribute to Agent Capabilities for mechanism of sending Agent Description

There is a requirement where we need Agent Description each time, as I understand opamp-spec is trying to optimize by not sending an Agent Description each time if there is no change.
Proposed Solution:
So, I would like to propose a solution where we can add in the Agent capabilities which can send Agent Description each time if it is required by the Server.
enum AgentCapabilities{
// ...
// Introduced ``Reporting agent description always`` trigger true/false - by default to keep it false
ReportAgentDescriptionAlways = 0x00002000;
}

@tigrannajaryan

The OpAMP server is supposed to track the state per agent (based on instance uid) and in that state the server can keep the agent capabilities. What is the use case where this is impossible?

read previous similar issue, so not to be considered for now

source: gharchive/issue

authors: kailash-bhanushali tigrannajaryan

repo: open-telemetry/opamp-spec


text:
Add link to opentelemetry.io under About section

Under the About section of this repo (which you can access from the main repo page -- click the gear icon next to the About title):

Under Website, replace the github.com link with https://opentelemetry.io
Or, if you prefer, you can link to https://opentelemetry.io/docs/instrumentation/erlang/

We're looking to do this uniformly for all OTel org repos.
For example:

Done

authors: bryannaegele chalin


text:
chore: do not export singletons

Fixes #38

I know that the headline tells do not export singletons. But above I read ... does not require that we export any no-op classes or singletons.
Currently NoopTextMapPropagator, NoopTracer,.. are still exported. Shoudl we remove them also?

authors: Flarna dyladan

repo: open-telemetry/opentelemetry-js-api


text:
chore(deps): upgrade @types/pino to be compatible with latest sonic-stream types

Which problem is this PR solving?

#591

Short description of the changes

upgrade @types/pino to 6.3.11

Does this still work for users using an older version of @types/pino?
A while ago we had a discussion if we should pin the version here or not. Or even use * to accept any version selected in the final app.

@Flarna Does this still work for users using an older version of @types/pino?

IIUC, types maintained in DefinitelyTyped versioned with the same minor.patch following the original package (see https://github.com/DefinitelyTyped/DefinitelyTyped#how-do-definitely-typed-package-versions-relate-to-versions-of-the-corresponding-library). If there are no mistakes, the version of type packages should follow semantic versioning.
I'm not sure which condition you are referring to. If you mean users that declared their own @types/pino dependencies in their package, as long as the user-defined version is compatible with the version defined in @opentelemetry/instrumentation-pino, it should be fine.

Or even use * to accept any version selected in the final app.

IIUC, the instrumentation package should set a version range of pino that it supports (like say, declare a set of version range in peer dependencies). A * sounds not great to me.

@types packages follow major.minor of their original. They may add/remove/rework definitions during this resulting in breakage like here. So in short @types packages don't follow semver (and this is documented at DefinitelyTyped).

I'm not sure which condition you are referring to. If you mean users that declared their own @types/pino dependencies in their package, as long as the user-defined version range is compatible with the version defined in @opentelemetry/instrumentation-pino, it should be fine.

I mean the version selected by the end user. @opentelemetry/instrumentation-pino uses a fixed version therefore a mismatch is likely. In that case NPM installs both versions (one as child of @opentelemetry/instrumentation-pino and one in the root node_modules folder).

Merging this since it is fixing the build which breaks in every PR

authors: Flarna dyladan legendecas

repo: open-telemetry/opentelemetry-js-contrib


text:
chore: release main

:robot: I have created a release *beep* *boop*
@opentelemetry/resource-detector-aws: 1.0.1
Bug Fixes

increase ec2 resource detector timeout (#722) (9855161)

This PR was generated with Release Please. See documentation.

@willarmiros @NathanielRN This only affects the AWS component right now. Would you like me to merge/release?

Sure I wouldn't mind :)

:robot: Release for @opentelemetry/resource-detector-aws is at https://github.com/open-telemetry/opentelemetry-js-contrib/releases/tag/resource-detector-aws-v1.0.1 :sunflower:

authors: dyladan willarmiros


text:
fix: avoid grpc types dependency

Which problem is this PR solving?
Please include a summary of the change and which issue is fixed. Please also include relevant motivation and context. List any dependencies that are required for this change.
Fixes #3548
Short description of the changes
Avoid a dependency to grpc types by moving the into a internal-types.ts file.
Type of change

[x] Bug fix (non-breaking change which fixes an issue)

How Has This Been Tested?
Local compile and look into resulting .d.ts files
Checklist:

[x] Followed the style guidelines of this project
[ ] Unit tests have been added
[ ] Documentation has been updated

Failing test seemed unrelated to this PR (looks like a network connectivity problem); it should be gone after the rebase :slightly_smiling_face:

@open-telemetry/javascript-maintainers  Any chance to move this forward? Currently contrib updates to latest SDK is blocked because of this.

@Flarna i'm back from vacation now i'll get this out asap

authors: Flarna dyladan pichlermarc

repo: open-telemetry/opentelemetry-js


text:
chore: OTel collector for exploratory testing

Reviewing and and performing exploratory testing PRs would be made easier by being able to visualize the results in a tracing backend.
This repository could provide contributors with an OTel collector service configured in the main docker-compose file like we do for other services.
Inspired by: https://github.com/open-telemetry/opentelemetry-ruby-contrib/pull/72#issuecomment-1170077416

Great idea!

authors: arielvalentin plantfansam


text:
Expose Collector component metadata in registry

Desired feature or idea: Components in the OpenTelemetry Collector repositories have a metadata.yaml file (example) that documents the stability of the component across several signals.
Stability definitions are available here and follow OTEP 232 definitions. Making this information available on the opentelemetry.io website would help users understand what components are mature enough to be used in their build depending on their requirements.
Additional context: We would like to have this information available in the registry for the Collector 1.0 distro.

I created https://github.com/open-telemetry/community/pull/2246 to address this project-wide, but independent of that, we should try to address this need from the collector SIG.
What we want to do boils down to merging the following two files:
https://github.com/open-telemetry/opentelemetry.io/blob/main/data/registry/collector-receiver-host-metrics.yml
and
https://github.com/open-telemetry/opentelemetry-collector-contrib/blob/main/receiver/hostmetricsreceiver/metadata.yaml
The easiest is probably taking the status from the metadata YML and copy it into the registry YML and then turn that into a workflow that checks for changes and transfers that to the otel.io repo.

authors: mx-psi svrnm


text:
Access to CNCF Cloud Native Community Groups platform

Access to CNCF Cloud Native Community Groups platform

Dan to raise Service Desk ticket
Rynn to create issue in community repo

@musingvirtual were you thinking of a community group in general for OTel end-users?

@danielgblanco to create ticket with Service Desk to:

[ ] Create an OpenTelemetry community group named "OpenTelemetry".
[ ] Confirm whether we can modify the page ourselves. Keptn's CG page as reference.
[ ] Share feedback about the Twitter/X API (makes it look very outdated).

On the above, I will initially add participants in this issue to the list of requested organisers of the group

Ticket created, I've not asked to include the organisers yet, but rather how organisers would be added (if via service desk or one organiser can add others)

Related to Twitter/X API and posts not up-to-date, I think we were too fast to RCA that :D Looking at https://x.com/CloudNativeFdn it seems that account (where community groups get their feed from) has not been active.

From support, regarding how to add people are organizers.

Each person that needs to be an organizer would need to create a profile on community.cncf.io and then you can share the list in this ticket and I will add them

Am I right in thinking organizers would be the following?

@avillela
@reese-lee
@musingvirtual
@danielgblanco

If you could create your profiles (see mine https://community.cncf.io/u/m5rbbe) I could then share them with the team to add us as organizers. This can later be modified, of course.

Done: https://community.cncf.io/u/m9783a/#/about

✅ https://community.cncf.io/u/mcxrj5/#/about

Thanks. @AnaMMedina21 and @IAMebonyhope when you have a chance, could you do the same? That way we can get all future end-user-sig-approvers (after team is created) as organizers in the community group

Here is mine: https://community.cncf.io/u/mbdek9/#/about

Here's mine: https://community.cncf.io/u/mg62up/#/about

Here is mine: https://community.cncf.io/u/myukru/

I've just asked for an update (still waiting on support)

I just got a "welcome new chapter organizer" (containing additional steps, so others might want to look for the email as well) so I am assuming they have done the thing!

I guess that just needed a reminder :) Page in https://community.cncf.io/opentelemetry so we'll consider this done!

authors: AnaMMedina21 IAMebonyhope avillela danielgblanco musingvirtual reese-lee

repo: open-telemetry/sig-end-user


text:
Proto restruct

View the proposed changes using the redocly API viewer
An overview of changes should go here along with any justifications.
config = api.config()
# sample interface, routers, flows configuration code here
api.set_config(config)

import otg
api = otg.api(location="https://localhost")
config = api.config()
p = config.ports.port(name='p1', location='localhost:5555')[-1]
p.name = "p2"
p.location  = 'localhost:5556'
Create 2 ethernet + ipv4 interfaces
intf1 = config.interfaces.interface(name='if1', container_name=p.name)[-1]
eth1= intf1.ethernet
eth1.name = 'eth1'
eth1.mac = '64:00:00:00:00:01'
eth1.vlans.vlan(name='vlan1', id=100)
ip1 = eth1.ipv4
ip1.name = 'ip1'
ip1.address = '1.1.1.1'
ip1.gateway = '1.1.1.10'
intf2 = config.interfaces.interface(name='if2', container_name=p.name)[-1]
eth2 = intf2.ethernet
eth2.name = 'eth2'
eth2.mac = '65:00:00:00:00:01'
eth2.vlans.vlan(name='vlan2', id=200)
ip2 = eth2.ipv4
ip2.name = 'ip2'
ip2.address = '2.1.1.1'
ip2.gateway = '2.1.1.10'
Create ISIS Router
rtr = config.routers.router(name='rtr')[-1]
isisRtr = rtr.isis
isisRtr.name = 'isis1'
isisRtr.system_id = '640000000001'
Create ISIS Interfaces
isisInf1 = isisRtr.interfaces.isisinterface(eth_name=eth1.name)[-1]
isisInf2 = isisRtr.interfaces.isisinterface(eth_name=eth2.name)[-1]
isisInf1.network_type = isisInf1.BROADCAST
isisInf2.network_type = isisInf2.POINT_TO_POINT
Create ISIS Router ranges
v4rr1 = isisRtr.isisv4_routes.isisv4route(name='rr1')[-1]
v4rr1.addresses.v4routeaddress(address='100.10.10.1', prefix=24, count=50, step=1)
v6rr1 = isisRtr.isisv6_routes.isisv6route(name='rr2')[-1]
v6rr1.addresses.v6routeaddress(address='2000::0', prefix=64, count=50, step=1)
print(config)

@ankur-sheth with this set of changes, how will a DP only case use the concept of interfaces and dynamically learn DMAC to emulate just simply a host? configure router.interfaces.ethernet?

That might be one option.  Need to give it some thought.

can we close this PR if we are not going with this approach?

closing as we converged on #154

authors: SuryyaKrJana ankur-sheth winstonliu1111

repo: open-traffic-generator/models


text:
Support for vxlan and Nested devices

Is your feature request related to a use case? Please describe.
BGP over EVPN VxLAN VxLan
Describe the solution you'd like
Need support in snapi for VxLan and adding chained device groups
Describe alternatives you've considered
RestPy
Additional context
We want to create below shown config.

.

Support is available in snappi[ixnetwork]==0.7.44

repo: open-traffic-generator/snappi-ixnetwork


text:
feat(lit-helpers): add spread directives

This introduces a new package, @open-wc/lit-helper, with two spread directives spread and spreadProps.
I considered adding spreadAttributes, but I felt that it wasn't needed because you can already use spread to do the same since there is no syntax difference for attributes.
Fixes https://github.com/open-wc/open-wc/issues/967

There is a section in the docs that explains why no spreadAttributes.
For sure spreading adds some overhead, it should only be used in scenario's where you just don't know all the keys. We can add a warning in the docs for that.

commitlint makes this PR appear red, but the commit will be squashed so it's fine.

should probably rebase manually to appease commitlint

authors: LarsDenBakker bennypowers

repo: open-wc/open-wc


text:
Is it possible to add a list or a chart in the admin backend to display the amount of requests for each model on the platform?

Is your feature request related to a problem? Please describe.
A clear and concise description of what the problem is. Ex. I'm always frustrated when [...]
Describe the solution you'd like
A clear and concise description of what you want to happen.
Describe alternatives you've considered
A clear and concise description of any alternative solutions or features you've considered.
Additional context
Add any other context or screenshots about the feature request here.

Duplicate #1450

authors: rhymecc tjbck

repo: open-webui/open-webui


text:
wrong response

I am new for llama3. Using Ollama + Docker + Open-webui for three days.
Suddently this morning all of llama3 response on open-webui always with {} when I input anything via open-webui but
normal on Ollama native mode. I tried to re-install everything but still got same issue.
Anyone can help ?

Make sure this is set to Default and not JSON:

yes, thank you. My mistake. Solved.

authors: jacksonlutw justinh-rahb


text:
Only admin can use model

As title, I just update to v0.4.7
and found only admin can see and use models.
Normal user can't ever see one, until I give him admin privileges
Normal user vision (it should be lots of model which I deploy):

I read all the settings but still can't solve it

Good Luck bro :).
Public means that the form is available to all users.

You're welcome, friend. We all make mistakes, but we learn. I wish you success.
I need a little help if you know where to put or upload the knowledge files and how to make the AI request a specific API or execute a specific script you can help me with any of the problems I face if you can or know how to solve them thank you.

I think "AI agent" is quite suitable for your needs.
It is used to request specific APIs or execute specific scripts in different situations.

Where can I find it on the interface? If possible, take a screenshot for me.

authors: AzizDXT ioveeagle


text:
Unsupported vlan-interface-current-performance LIVE API to be removed from MWDI .

Unsupported vlan-interface-current-performance API to be removed from MWDI live.
/core-model-1-4:network-control-domain=live/control-construct={mountName}/logical-termination-point={uuid}/layer-protocol={localId}/vlan-interface-1-0:vlan-interface-pac/vlan-interface-current-performance

When tried to execute the API its throwing 409 conflict error

http://xxx:xxx/core-model-1-4:network-control-domain=live/control-construct=513250010/logical-termination-point=VI-10/layer-protocol=10/vlan-interface-1-0:vlan-interface-pac/vlan-interface-current-performance
Error:
{
  "code": 409,
  "message": "Conflict"
}

As per the YANG , vlan-interface-current-performance attribute is not supported.
But in MWDI , LIVE we are able to see the API for vlan-interface-current-performance . Please remove it from swagger.

API entries have been removed from spec (see #913)

Tested with MWDI latest version test_v1.1.5.
Issue is no longer observed. vlan-interface-current-performance ( domain=live)  API removed from swagger

Tested OKAY with MWDI latest version test_v1.1.5.

authors: Ziabatcha kmohr-soprasteria

repo: openBackhaul/MicroWaveDeviceInventory


text:
🛑 Server is down

In b02de8a, Server ($SERVER_SITE_GET_ENDPOINT) was down:

HTTP code: 0
Response time: 0 ms

Resolved: Server is back up in 4f54a8f.

repo: openCONTRABASS/upptime-server


text:
bug: Navigation item remains selected even for the screens which aren't in app

Summary:
bug: Navigation item remains selected even for the screens which aren't in app which leads to confusion as to figure out which screen we are on.
Steps to reproduce:
Open App, Nav drawer, click on Charges (Example). We remain on the Home Screen.
Expected behaviour:
Nav drawer should close with the actual item highlighted.
Observed behaviour:
The wrong item remains highlighted.
Screenshots:
I would work on this.

@naman14 @AbhilashG97 @therajanmaurya Can I go ahead?

I'll be working on it.

repo: openMF/mifos-mobile-cn


text:
Close  #115: Allow user to store non-openPMD information

Close #115: This allows user to store additional data, outside of the basePath.

thx for the PR! :)

Thanks for the comments! I updated the PR.

repo: openPMD/openPMD-standard


text:
Upload Osceola, FL data to s3

Until https://github.com/openaddresses/machine/issues/325 is supported, please upload the attached file to s3.
osceola.fl.zip
Needed for #1619

Uploaded: http://data.openaddresses.io/cache/us-fl-osceola.zip

authors: ingalls trescube

repo: openaddresses/openaddresses


text:
Bahamas Address Points

https://drive.google.com/file/d/1_JU35QwDozHTa4dPMlX8cyw_YHXg4C1F/view?usp=sharing
Licensing
The data supplied in the repo is provided by the Grand Bahama Port Authority (GBPA) for third parties to use or modify under a Creative Commons Attribution 4.0 International (CC BY 4.0) license. Please include "Data Provided by The Grand Bahama Port Authority" in both the source code and UI of your application where possible.
@ingalls let me know when you grab this so i can delete it from my google drive. Thanks!!

@ingalls or here: https://services5.arcgis.com/2A67EqGJx1Goyk7B/ArcGIS/rest/services/Address_points_Freeport_WGS84_LatLong/FeatureServer


text:
Install Baselines

When I install Baseline,
Command "/usr/bin/python3 -u -c "import setuptools, tokenize;file='/tmp/pip-install-p2poh3ol/mpi4py/setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" install --record /tmp/pip-record-zamwt56h/install-record.txt --single-version-externally-managed --compile" failed with error code 1 in /tmp/pip-install-p2poh3ol/mpi4py/

Please give far more information about your machine and setup so that others can reproduce or trace your steps.

fixed problems,
thanks

new comer here, same problem.how did you fix that?

new comer here, same problem.how did you fix that?

fixed problems,
thanks

authors: DanielTakeshi Nara0731 ruyueshuo

repo: openai/baselines

license: mit


text:
createImage function no longer working

Describe the bug
The createImage function was working fine in my Node.js web app until the last couple of days. Now I get an error when trying to execute it.
To Reproduce

Call createImage function

See error

Error:
Error: Request failed with status code 400
at createError (C:\Web dev\practiceReact\ImageGeneratorAI\server\node_modules\openai\node_modules\axios\lib\core\createError.js:16:15)
at settle (C:\Web dev\practiceReact\ImageGeneratorAI\server\node_modules\openai\node_modules\axios\lib\core\settle.js:17:12)
at IncomingMessage.handleStreamEnd (C:\Web dev\practiceReact\ImageGeneratorAI\server\node_modules\openai\node_modules\axios\lib\adapters\http.js:322:11)
at IncomingMessage.emit (node:events:525:35)
at endReadableNT (node:internal/streams/readable:1359:12)
at process.processTicksAndRejections (node:internal/process/task_queues:82:21) {
config: {
transitional: {
silentJSONParsing: true,
forcedJSONParsing: true,
clarifyTimeoutError: false
},
adapter: [Function: httpAdapter],
transformRequest: [ [Function: transformRequest] ],
transformResponse: [ [Function: transformResponse] ],
timeout: 0,
xsrfCookieName: 'XSRF-TOKEN',
xsrfHeaderName: 'X-XSRF-TOKEN',
maxContentLength: -1,
maxBodyLength: -1,
validateStatus: [Function: validateStatus],
headers: {
Accept: 'application/json, text/plain, /',
'Content-Type': 'application/json',
'User-Agent': 'OpenAI/NodeJS/3.1.0',
Authorization: 'Bearer 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',
'Content-Length': 128
},
method: 'post',
data: '{"prompt":"A centered explosion of colorful powder on a black background","n":1,"size":"1024x1024","response_format":"b64_json"}',
url: 'https://api.openai.com/v1/images/generations'
},
request: <ref *1> ClientRequest {
_events: [Object: null prototype] {
abort: [Function (anonymous)],
aborted: [Function (anonymous)],
connect: [Function (anonymous)],
error: [Function (anonymous)],
socket: [Function (anonymous)],
timeout: [Function (anonymous)],
finish: [Function: requestOnFinish]
},
_eventsCount: 7,
_maxListeners: undefined,
outputData: [],
outputSize: 0,
writable: true,
destroyed: false,
_last: true,
chunkedEncoding: false,
shouldKeepAlive: false,
maxRequestsOnConnectionReached: false,
_defaultKeepAlive: true,
useChunkedEncodingByDefault: true,
sendDate: false,
_removedConnection: false,
_removedContLen: false,
_removedTE: false,
strictContentLength: false,
_contentLength: 128,
_hasBody: true,
_trailer: '',
finished: true,
_headerSent: true,
_closed: false,
socket: TLSSocket {
_tlsOptions: [Object],
_secureEstablished: true,
_securePending: false,
_newSessionPending: false,
_controlReleased: true,
secureConnecting: false,
_SNICallback: null,
servername: 'api.openai.com',
alpnProtocol: false,
authorized: true,
authorizationError: null,
encrypted: true,
_events: [Object: null prototype],
_eventsCount: 10,
connecting: false,
_hadError: false,
_parent: null,
_host: 'api.openai.com',
_closeAfterHandlingError: false,
_readableState: [ReadableState],
_maxListeners: undefined,
_writableState: [WritableState],
allowHalfOpen: false,
_sockname: null,
_pendingData: null,
_pendingEncoding: '',
server: undefined,
_server: null,
ssl: [TLSWrap],
_requestCert: true,
_rejectUnauthorized: true,
parser: null,
_httpMessage: [Circular *1],
[Symbol(res)]: [TLSWrap],
[Symbol(verified)]: true,
[Symbol(pendingSession)]: null,
[Symbol(async_id_symbol)]: 1427,
[Symbol(kHandle)]: [TLSWrap],
[Symbol(lastWriteQueueSize)]: 0,
[Symbol(timeout)]: null,
[Symbol(kBuffer)]: null,
[Symbol(kBufferCb)]: null,
[Symbol(kBufferGen)]: null,
[Symbol(kCapture)]: false,
[Symbol(kSetNoDelay)]: false,
[Symbol(kSetKeepAlive)]: true,
[Symbol(kSetKeepAliveInitialDelay)]: 60,
[Symbol(kBytesRead)]: 0,
[Symbol(kBytesWritten)]: 0,
[Symbol(connect-options)]: [Object]
},
_header: 'POST /v1/images/generations HTTP/1.1\r\n' +
'Accept: application/json, text/plain, /\r\n' +
'Content-Type: application/json\r\n' +
'User-Agent: OpenAI/NodeJS/3.1.0\r\n' +
'Authorization: Bearer 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\r\n' +
'Content-Length: 128\r\n' +
'Host: api.openai.com\r\n' +
'Connection: close\r\n' +
'\r\n',
_keepAliveTimeout: 0,
_onPendingData: [Function: nop],
agent: Agent {
_events: [Object: null prototype],
_eventsCount: 2,
_maxListeners: undefined,
defaultPort: 443,
protocol: 'https:',
options: [Object: null prototype],
requests: [Object: null prototype] {},
sockets: [Object: null prototype],
freeSockets: [Object: null prototype] {},
keepAliveMsecs: 1000,
keepAlive: false,
maxSockets: Infinity,
maxFreeSockets: 256,
scheduling: 'lifo',
maxTotalSockets: Infinity,
totalSocketCount: 1,
maxCachedSessions: 100,
_sessionCache: [Object],
[Symbol(kCapture)]: false
},
socketPath: undefined,
method: 'POST',
maxHeaderSize: undefined,
insecureHTTPParser: undefined,
joinDuplicateHeaders: undefined,
path: '/v1/images/generations',
_ended: true,
res: IncomingMessage {
_readableState: [ReadableState],
_events: [Object: null prototype],
_eventsCount: 4,
_maxListeners: undefined,
socket: [TLSSocket],
httpVersionMajor: 1,
httpVersionMinor: 1,
httpVersion: '1.1',
complete: true,
rawHeaders: [Array],
rawTrailers: [],
joinDuplicateHeaders: undefined,
aborted: false,
upgrade: false,
url: '',
method: null,
statusCode: 400,
statusMessage: 'Bad Request',
client: [TLSSocket],
_consuming: false,
_dumped: false,
req: [Circular *1],
responseUrl: 'https://api.openai.com/v1/images/generations',
redirects: [],
[Symbol(kCapture)]: false,
[Symbol(kHeaders)]: [Object],
[Symbol(kHeadersCount)]: 28,
[Symbol(kTrailers)]: null,
[Symbol(kTrailersCount)]: 0
},
aborted: false,
timeoutCb: null,
upgradeOrConnect: false,
parser: null,
maxHeadersCount: null,
reusedSocket: false,
host: 'api.openai.com',
protocol: 'https:',
_redirectable: Writable {
_writableState: [WritableState],
_events: [Object: null prototype],
_eventsCount: 3,
_maxListeners: undefined,
_options: [Object],
_ended: true,
_ending: true,
_redirectCount: 0,
_redirects: [],
_requestBodyLength: 128,
_requestBodyBuffers: [],
_onNativeResponse: [Function (anonymous)],
_currentRequest: [Circular 1],
_currentUrl: 'https://api.openai.com/v1/images/generations',
[Symbol(kCapture)]: false
},
[Symbol(kCapture)]: false,
[Symbol(kBytesWritten)]: 0,
[Symbol(kEndCalled)]: true,
[Symbol(kNeedDrain)]: false,
[Symbol(corked)]: 0,
[Symbol(kOutHeaders)]: [Object: null prototype] {
accept: [Array],
'content-type': [Array],
'user-agent': [Array],
authorization: [Array],
'content-length': [Array],
host: [Array]
},
[Symbol(errored)]: null,
[Symbol(kUniqueHeaders)]: null
},
response: {
status: 400,
statusText: 'Bad Request',
headers: {
date: 'Tue, 04 Apr 2023 22:32:41 GMT',
'content-type': 'application/json',
'content-length': '172',
connection: 'close',
'access-control-allow-origin': '',
'openai-version': '2020-10-01',
'openai-organization': 'user-hohs5y1guudtogkf6k2glor8',
'x-request-id': '86461dbb395a0e7c0855a07197923f09',
'openai-processing-ms': '96',
'strict-transport-security': 'max-age=15724800; includeSubDomains',
'cf-cache-status': 'DYNAMIC',
server: 'cloudflare',
'cf-ray': '7b2d023b8a7a4911-LHR',
'alt-svc': 'h3=":443"; ma=86400, h3-29=":443"; ma=86400'
},
config: {
transitional: [Object],
adapter: [Function: httpAdapter],
transformRequest: [Array],
transformResponse: [Array],
timeout: 0,
xsrfCookieName: 'XSRF-TOKEN',
xsrfHeaderName: 'X-XSRF-TOKEN',
maxContentLength: -1,
maxBodyLength: -1,
validateStatus: [Function: validateStatus],
headers: [Object],
method: 'post',
data: '{"prompt":"A centered explosion of colorful powder on a black background","n":1,"size":"1024x1024","response_format":"b64_json"}',
url: 'https://api.openai.com/v1/images/generations'
},
request: <ref *1> ClientRequest {
_events: [Object: null prototype],
_eventsCount: 7,
_maxListeners: undefined,
outputData: [],
outputSize: 0,
writable: true,
destroyed: false,
_last: true,
chunkedEncoding: false,
shouldKeepAlive: false,
maxRequestsOnConnectionReached: false,
_defaultKeepAlive: true,
useChunkedEncodingByDefault: true,
sendDate: false,
_removedConnection: false,
_removedContLen: false,
_removedTE: false,
strictContentLength: false,
_contentLength: 128,
_hasBody: true,
_trailer: '',
finished: true,
_headerSent: true,
_closed: false,
socket: [TLSSocket],
_header: 'POST /v1/images/generations HTTP/1.1\r\n' +
'Accept: application/json, text/plain, /\r\n' +
'Content-Type: application/json\r\n' +
'User-Agent: OpenAI/NodeJS/3.1.0\r\n' +
'Authorization: Bearer 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\r\n' +
'Content-Length: 128\r\n' +
'Host: api.openai.com\r\n' +
'Connection: close\r\n' +
'\r\n',
_keepAliveTimeout: 0,
_onPendingData: [Function: nop],
agent: [Agent],
socketPath: undefined,
method: 'POST',
maxHeaderSize: undefined,
insecureHTTPParser: undefined,
joinDuplicateHeaders: undefined,
path: '/v1/images/generations',
_ended: true,
res: [IncomingMessage],
aborted: false,
timeoutCb: null,
upgradeOrConnect: false,
parser: null,
maxHeadersCount: null,
reusedSocket: false,
host: 'api.openai.com',
protocol: 'https:',
_redirectable: [Writable],
[Symbol(kCapture)]: false,
[Symbol(kBytesWritten)]: 0,
[Symbol(kEndCalled)]: true,
[Symbol(kNeedDrain)]: false,
[Symbol(corked)]: 0,
[Symbol(kOutHeaders)]: [Object: null prototype],
[Symbol(errored)]: null,
[Symbol(kUniqueHeaders)]: null
},
data: { error: [Object] }
},
isAxiosError: true,
toJSON: [Function: toJSON]
}
The function in the server which executes the createImage function:
import * as dotenv from 'dotenv'
import { Configuration, OpenAIApi } from 'openai'

dotenv.config()

const configuration = new Configuration({
    apiKey: process.env.OPENAI_API_KEY
})

const openai = new OpenAIApi(configuration)

export const CreateImage = async(req, res) =>
{
    try
    {
        const prompt = req.body.prompt

        //Doesn't work
        const aiResponse = await openai.createImage({
            prompt,
            n:1,
            size: '1024x1024',
            response_format: 'b64_json'
        })

        const image = aiResponse.data.data[0].b64_json

        res.status(200).json({ photo: image })
    }
    catch (err)
    {
        console.log(err)
        res.status(500).send(err?.response.data.error.message)
    }
}

OS
Windows 10
Node version
Node v18.14.1
Library version
openai v3.1.0

It has happened for me also @hasnat123
Please let me know if you've found the fix

We have a new version of the library coming up: https://github.com/openai/openai-node/discussions/182
Can you give that a try and see it solves the issue?

Hey @rattrayalex
Thanks for replying! I found out why i was facing the issue. I was unaware of the billing system and looks like I have exhausted my free credit limit.
nevertheless, thx again mate

authors: hasnat123 himikasarkar rattrayalex

repo: openai/openai-node


text:
ImportError: ... go_vncdriver.so: no suitable image found.  Did find: ...go_vncdriver.so: overlapping segments

Expected behavior
universe is imported without errors from Python 3.5's console.
Actual behavior
Python 3.5.0 (v3.5.0:374f501f4567, Sep 12 2015, 11:00:19)
[GCC 4.2.1 (Apple Inc. build 5666) (dot 3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> import universe
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/cell/Desktop/tests/universe/universe/__init__.py", line 22, in <module>
    from universe import error, envs
  File "/Users/cell/Desktop/tests/universe/universe/envs/__init__.py", line 1, in <module>
    import universe.envs.vnc_env
  File "/Users/cell/Desktop/tests/universe/universe/envs/vnc_env.py", line 19, in <module>
    import go_vncdriver
  File "/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/go_vncdriver/__init__.py", line 9, in <module>
    from go_vncdriver.go_vncdriver import *
ImportError: dlopen(/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/go_vncdriver/go_vncdriver.so, 2): no suitable image found.  Did find:
	/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/go_vncdriver/go_vncdriver.so: overlapping segments
	/Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages/go_vncdriver/go_vncdriver.so: overlapping segments

Versions
Darwin Nelsons-MacBook-Pro.local 16.7.0 Darwin Kernel Version 16.7.0: Thu Jun 15 17:36:27 PDT 2017; root:xnu-3789.70.16~2/RELEASE_X86_64 x86_64
Python 3.5.0
Name: universe
Version: 0.21.5
Summary: Universe: a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications.
Home-page: https://github.com/openai/universe
Author: OpenAI
Author-email: universe@openai.com
License: UNKNOWN
Location: /Users/cell/Desktop/tests/universe
Requires: autobahn, docker-py, docker-pycreds, fastzbarlight, go-vncdriver, gym, Pillow, PyYAML, six, twisted, ujson
---
Name: gym
Version: 0.9.3
Summary: The OpenAI Gym: A toolkit for developing and comparing your reinforcement learning agents.
Home-page: https://github.com/openai/gym
Author: OpenAI
Author-email: gym@openai.com
License: UNKNOWN
Location: /Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages
Requires: numpy, requests, six, pyglet
---
Name: tensorflow
Version: 1.3.0
Summary: TensorFlow helps the tensors flow
Home-page: http://tensorflow.org/
Author: Google Inc.
Author-email: opensource@google.com
License: Apache 2.0
Location: /Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages
Requires: tensorflow-tensorboard, six, wheel, numpy, protobuf
---
Name: numpy
Version: 1.13.1
Summary: NumPy: array processing for numbers, strings, records, and objects.
Home-page: http://www.numpy.org
Author: NumPy Developers
Author-email: numpy-discussion@python.org
License: BSD
Location: /Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages
Requires:
---
Name: go-vncdriver
Version: 0.4.19
Summary: UNKNOWN
Home-page: UNKNOWN
Author: UNKNOWN
Author-email: UNKNOWN
License: UNKNOWN
Location: /Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages
Requires: numpy
---
Name: Pillow
Version: 4.2.1
Summary: Python Imaging Library (Fork)
Home-page: https://python-pillow.org
Author: Alex Clark (Fork Author)
Author-email: aclark@aclark.net
License: Standard PIL License
Location: /Library/Frameworks/Python.framework/Versions/3.5/lib/python3.5/site-packages
Requires: olefile

I want to try universe. I'm following this guide. I ran the following commands:
git clone https://github.com/openai/universe
sudo pip install -e universe

I run pip with sudo because I was having some "permission errors". Then I also executed the following command:
sudo docker run --privileged --cap-add=SYS_ADMIN --ipc=host -p 5900:5900 -p 15900:15900 quay.io/openai/universe.flashgames

And I keep receiving messages on the terminal (I guess, as expected).
Now, I was trying to run the following code
import gym
import universe # register Universe environments into Gym

env = gym.make('flashgames.DuskDrive-v0') # any Universe [environment ID](https://github.com/openai/universe/blob/master/universe/__init__.py#L297) here
# If using docker-machine, replace "localhost" with your Docker IP
env.configure(remotes="vnc://localhost:5900+15900")
observation_n = env.reset()

while True:
  # agent which presses the Up arrow 60 times per second
  action_n = [[('KeyEvent', 'ArrowUp', True)] for _ in observation_n]
  observation_n, reward_n, done_n, info = env.step(action_n)
  env.render()

saved in a file run.py using python3.5, but I get the same error as the one I'm describing above when trying to import universe. The reason I'm using python3.5 instead of python is because python is actually attached to a  Python2.7 distribution.

Same error as in https://github.com/openai/universe/issues/167.

@gdb Why did you close this issue? At least, I think, you should add a comment to this issue stating that a solution is explained in the other issue.

repo: openai/universe


text:
[REQ][python] Improve generated new input type for anyOf schema

Bug Report Checklist

[x] Have you provided a full/minimal spec to reproduce the issue?
[x] Have you validated the input using an OpenAPI validator (example)?
[x] Have you tested with the latest master to confirm the issue still exists?
[x] Have you searched for related issues/PRs?
[x] What's the actual output vs expected output?
[ ] [Optional] Sponsorship to speed up the bug fix or feature request

Description
When having an anyOf modifier for a schema that is used in a array schema, the resulting python class does not have the correct typing.
Given the following schemas
    ClassificationToReturn:
      properties:
        name:
          type: string
          minLength: 3
        displayName:
          type: string
        exportName:
          type: string
          nullable: true
          minLength: 1
        attributes:
          items:
            $ref: "#/components/schemas/ClassificationAttribute"
          type: array
    ClassificationAttribute:
      $ref: "#/components/schemas/SingleValueClassificationAttribute"
    SingleValueClassificationAttribute:
      properties:
        name:
          type: string
          minLength: 1
          pattern: ^[^.]+$
        displayName:
          type: string
          minLength: 1
        exportName:
          type: string
          minLength: 1
      required:
        - name
      type: object
      additionalProperties: false
    MultiValueClassificationAttribute:
      properties:
        name:
          type: string
          minLength: 1
        maximumCount:
          type: integer
          format: int32
          minimum: 0
      required:
        - name
      type: object
      additionalProperties: false

the created class (in classification_to_return.py) has the correct typing information
class AttributesTuple(
    typing.Tuple[
        classification_attribute.single_value_classification_attribute.SingleValueClassificationAttributeDict,
        ...
    ]
):

    def __new__(cls, arg: typing.Union[AttributesTupleInput, AttributesTuple], configuration: typing.Optional[schema_configuration.SchemaConfiguration] = None):
        return Attributes.validate(arg, configuration=configuration)
AttributesTupleInput = typing.Union[
    typing.List[
        typing.Union[
            classification_attribute.single_value_classification_attribute.SingleValueClassificationAttributeDictInput,
            classification_attribute.single_value_classification_attribute.SingleValueClassificationAttributeDict,
        ],
    ],
    typing.Tuple[
        typing.Union[
            classification_attribute.single_value_classification_attribute.SingleValueClassificationAttributeDictInput,
            classification_attribute.single_value_classification_attribute.SingleValueClassificationAttributeDict,
        ],
        ...
    ]
]

@dataclasses.dataclass(frozen=True)
class Attributes(
    schemas.Schema[schemas.immutabledict, AttributesTuple]
):
    types: typing.FrozenSet[typing.Type] = frozenset({tuple})
    items: typing.Type[classification_attribute.ClassificationAttribute] = dataclasses.field(default_factory=lambda: classification_attribute.ClassificationAttribute) # type: ignore
    type_to_output_cls: typing.Mapping[
        typing.Type,
        typing.Type
    ] = dataclasses.field(
        default_factory=lambda: {
            tuple: AttributesTuple
        }
    )

However, when we use an anyOf in ClassificationAttribute
      ClassificationToReturn:
        properties:
          name:
            type: string
            minLength: 3
          displayName:
            type: string
          exportName:
            type: string
            nullable: true
            minLength: 1
          attributes:
            items:
              $ref: "#/components/schemas/ClassificationAttribute"
            type: array
      ClassificationAttribute:
        anyOf:
          - $ref: "#/components/schemas/SingleValueClassificationAttribute"
          - $ref: "#/components/schemas/MultiValueClassificationAttribute"
      SingleValueClassificationAttribute:
        properties:
          name:
            type: string
            minLength: 1
            pattern: ^[^.]+$
          displayName:
            type: string
            minLength: 1
          exportName:
            type: string
            minLength: 1
        required:
          - name
        type: object
        additionalProperties: false
      MultiValueClassificationAttribute:
        properties:
          name:
            type: string
            minLength: 1
          maximumCount:
            type: integer
            format: int32
            minimum: 0
        required:
          - name
        type: object
        additionalProperties: false

we will get the wrong typing information in classification_to_return.py
class AttributesTuple(
    typing.Tuple[
        schemas.OUTPUT_BASE_TYPES,
        ...
    ]
):

    def __new__(cls, arg: typing.Union[AttributesTupleInput, AttributesTuple], configuration: typing.Optional[schema_configuration.SchemaConfiguration] = None):
        return Attributes.validate(arg, configuration=configuration)
AttributesTupleInput = typing.Union[
    typing.List[
        typing.Union[
            schemas.INPUT_TYPES_ALL,
            schemas.OUTPUT_BASE_TYPES
        ],
    ],
    typing.Tuple[
        typing.Union[
            schemas.INPUT_TYPES_ALL,
            schemas.OUTPUT_BASE_TYPES
        ],
        ...
    ]
]

@dataclasses.dataclass(frozen=True)
class Attributes(
    schemas.Schema[schemas.immutabledict, AttributesTuple]
):
    types: typing.FrozenSet[typing.Type] = frozenset({tuple})
    items: typing.Type[classification_attribute.ClassificationAttribute] = dataclasses.field(default_factory=lambda: classification_attribute.ClassificationAttribute) # type: ignore
    type_to_output_cls: typing.Mapping[
        typing.Type,
        typing.Type
    ] = dataclasses.field(
        default_factory=lambda: {
            tuple: AttributesTuple
        }
    )

The AttributesTuple should have the type information ClassificationAttribute or at least both of the possible types.

openapi-json-schema-generator version
Version 4.5.1

OpenAPI declaration file content or url

Generation Details
Used the cli command to generate the client.

Steps to reproduce

Related issues/PRs

Suggest a fix

The code generation is functioning as expected here. The anyOf refs are not known as possible types. For them to be known they would have to be examined at one higher schema level and compared against type info. Currently the generation only knows about input and output types for array and object, types defined in type, and ref only. Because anyOf is not analyzed for type info, the only info comes from absent type info which allows any type.
If you want different functionality here, please consider filing a PR with thorough test cases.

Also, should your anyOf be a oneOf so it matches only one of those schemas rather than one or more?

Thanks for the information. Is it possible to have a short meeting or could you point out the necessary steps for such functionality? We would like to invest some time to add such feature as our use case prefers to work with these classes and it would be nice to have proper type hints. However, we cannot really judge how long it may take.

Also, should your anyOf be a oneOf so it matches only one of those schemas rather than one or more?

You are right. Our openAPI.yaml is also auto-generated which sometime causes semantically wrong specification like this.

Adding this is non-trivial.
In the latest version of the generators, returned instances only subclass one class. So to do this one would need to:

perhaps generate interfaces for all object types and have the object output classes implement them
accumulate type + interface/dict output class info from all subschemas
for use cases like this, the code will know from introspecting the calculated type constraints that only dicts are allowed. And we know that the oneOf interfaces or output types are allowed

Doing this is difficult because any number of keywords can exist in the same schema including:

type
oneOf
allOf
etc and type and interface information need to be gathered from them and correctly combined

So a new CodegenSchema field that could store this may look like typeToInterfaces: Map<String, List>
Interfaces can come from refed locations so one would need to store the ref location and the name of the generated interface class. Some examples:
typeToInterfaces = {"string": null, "boolean": null} # fora a schema that allows strings and numbers
typeToInterfaces = {"object": [{SingleValueClassificationAttributeInterface, MultiValueClassificationAttributeInterface}]} # for your use case
This property would need to be added to CodegenSchema.
When are you free to discuss this this week and next week?

Hey, I am free this week. How should we proceed? I can write you a mail to figure out a date. A coworker would potentially join the meeting.

A simpler solution here is to handle this specific cas eonly where a schema only has oneOf defintion and no other json schema keywords. In this case, you could modify the Schema.validate method to do the following:

run validation on the payload and get back the list if [schema_containing_oneof, specific_oneof_schema]
and then use the last class specific_oneof_schema, as the class that is produced (instantiated)
other needed changes (for only this simple oneOf use case )

modify new input to accept union of oneoOf typeddicts and map output classes
modify new output to product union of oneof output classes

@Marcelo00 how did you decide to proceed forward here?
It has been ~ 1 month since we met about this.

If I don't hear back here I will close this issue as inactive.

Hey, I am sorry for not coming back to you. We tried out your suggestion of using speakeasy and it turns out that I fulfills our requirements. Thanks again for your time investing in this project and your suggestion. Really appreciate your help.


text:
[REQUEST] Extensions support for selenium

requesting for extensions support for selenium

Duplicate of https://github.com/openbullet/OpenBullet2/issues/762

authors: openbullet timolarra


text:
bin/opencfp cache:clear throws exception

Steps required to reproduce the problem

Set up project, install dependencies, etc.
Run bin/opencfp cache:clear

Expected Result

Expect all caches to be cleared.

Actual Result
mdwheele@28d9116def76:/usr/src/app$ bin/opencfp cache:clear

OpenCFP
=======

Clearing caches
---------------

  * /usr/src/app/cache/development (214 files and directories)

 [OK] Cleared caches.

Warning: Uncaught Symfony\Component\Debug\Exception\ContextErrorException: Warning: require(/usr/src/app/cache/development/ContainerCxf10iq/getSwiftmailer_EmailSender_ListenerService.php): failed to open stream: No such file or directory in /usr/src/app/cache/development/ContainerCxf10iq/OpenCFPDevelopmentDebugProjectContainer.php:543
Stack trace:
#0 /usr/src/app/cache/development/ContainerCxf10iq/OpenCFPDevelopmentDebugProjectContainer.php(543): require()
#1 /usr/src/app/cache/development/ContainerCxf10iq/OpenCFPDevelopmentDebugProjectContainer.php(948): ContainerCxf10iq\OpenCFPDevelopmentDebugProjectContainer->load('/usr/src/app/ca...')
#2 /usr/src/app/vendor/symfony/event-dispatcher/EventDispatcher.php(229): ContainerCxf10iq\OpenCFPDevelopmentDebugProjectContainer->ContainerCxf10iq\{closure}()
#3 /usr/src/app/vendor/symfony/event-dispatcher/EventDispatcher.php(61): Symfony\Component\EventDispatcher\EventDispatcher->sortListeners('console.termina...')
#4 /usr/src/app/vendor/symfony/event-dispatcher/ContainerAwareEve in /usr/src/app/cache/development/ContainerCxf10iq/OpenCFPDevelopmentDebugProjectContainer.php on line 543

Fatal error: ContainerCxf10iq\OpenCFPDevelopmentDebugProjectContainer::load(): Failed opening required '/usr/src/app/cache/development/ContainerCxf10iq/getSwiftmailer_EmailSender_ListenerService.php' (include_path='.:/usr/local/lib/php') in /usr/src/app/cache/development/ContainerCxf10iq/OpenCFPDevelopmentDebugProjectContainer.php on line 543

In OpenCFPDevelopmentDebugProjectContainer.php line 543:

  [Symfony\Component\Debug\Exception\FatalErrorException]
  Compile Error: ContainerCxf10iq\OpenCFPDevelopmentDebugProjectContainer::load(): Failed opening required '/usr/src/app/cache/development/ContainerCxf10iq/getSwiftmailer_EmailSender_ListenerService.ph
  p' (include_path='.:/usr/local/lib/php')

Exception trace:

cache:clear [-h|--help] [-q|--quiet] [-v|vv|vvv|--verbose] [-V|--version] [--ansi] [--no-ansi] [-n|--no-interaction] [--env ENV] [--] <command>

Not being familiar with Symfony, I assume it's clearing cache and then something else is expecting to require a file that was cleared to do work. I can dig in later. I spent 5 minutes wondering why my settings weren't updating and remembered "Oh yeah... container cache... it's a thing now."

Okay, sorry for that.
Symfony has its own cache:clear command.
We should add the regular Symfony console to the project, which would also expose some helpful debug commands. That console also has a cache:clear command which probably works better than my naive implementation.
We could even merge our commands into the Symfony console, but then we would give the user way more commands than he asked for.

No worries! I was only making note as I was relearning the project :grin:
I think adding our commands to the standard Symfony console would be fine.

authors: derrabus mdwheele

repo: opencfp/opencfp


text:
Fixed javadocs

PR for #282
Fixed javadocs so maven-javadoc-plugin won't complain anymore.

Coverage remained the same at 80.022% when pulling 5c4b99c575e73dec6c7afe120ce0c9e15a8b8b61 on 282 into 6a954485218c00ee0198fd99454f736bae778d54 on master.

@rultor merge it pls

@rultor merge it pls

@amihaiemil OK, I'll try to merge now. You can check the progress of the merge here

@rultor merge it pls

@amihaiemil Done! FYI, the full log is here (took me 3min)

authors: amihaiemil coveralls rultor

repo: opencharles/charles-rest


text:
Bug Fix

Previously the Logout feature of the navigation drawer was working but not it is not. Find out the bug and resolve it so that the logout option asks the user in a dialog box if they're sure they want to logout or not and the yes and no options should also pop up.

claim

assigned @IEC2021103Abhinav

repo: opencodeiiita/SuperQuizzer


text:
Confusing error message 'no payment method avialable' when contributing using a Collective balance between hosts

Describe the bug
When contributing to Collectives I can select my Collective/Fund as the payment method if the Collective receiving my contribution is using the same host.  If the Collective is on a different host I get a confusing error message

No payment methods available

The problem is in fact that the payment method is not available for this particular transaction because of the situation described. This is confusing and we can do a better job by providing a more accurate error message:

The payment methods below are unavailable for this transaction

With the Collective balance greyed out (but present)
To Reproduce
Steps to reproduce the behavior:
Create a collective hosted by host X
Create a collective hosted by host Y
Add a positive balance to collective hosted by X
Contribute to collective hosted by Y from X
Select Collective X as contributor, click next
... Profit.

Expected behaviour
I should be aware that my balance cannot be used for this particular transaction.
I should be directed to contribute using another payment method (Card, PayPal, bank transfer)
Triage
P2 low frequency, high impact

This we have worked previously and a bit of a complicated issue to solve completely I believe. For further clarification refer; https://github.com/opencollective/opencollective/issues/4669#issuecomment-920799739. I would close this and track this in the other issue; but if you feel there's anything different between this and that issue feel free to re-open. 🙂

authors: BenJam SudharakaP

repo: opencollective/opencollective


text:
The ability to show or hide expense comments

User story
_A collective admin would like the ability to show expense comments "We would prefer that all expenses be documented openly so that we are as public as possible. It appears that the initial note is private and cannot be made public to provide supporting detail for an expense. Is there a possibility that this could be configurable, for organizations such as ours?"
Best solution for this problem
_Toggl option to turn expense comments publicity on and off

Triage Template (team only)
This template is for members of the team to triage for prioritisation. For more guidance see https://www.loom.com/share/369ab467fbc64dec848085d38ff57ca0:
P1 high frequency, high impact
P2 low frequency, high impact
P3 high frequency, low impact
P4 low frequency, low impact
Examples of high impact - a problem affects users during an essential process (expenses and payments > onboarding and registration > contributing) with no workaround.
High frequency - >10% of users affected (measured as a proportion of total potential users for this case).

We decided a while ago that expense comments needed to be private because users tended to reply with payment information in there.
I'd be concerned about the risk of data exposure if we decide to let host admins change this. Even if we add proper warnings, someone used to the platform with another fiscal host could for example go too fast while replying and not notice that this new fiscal host they're submitting their invoice to has expense comments public, and paste private information there.
Maybe we can think about another way to solve this that is less risky in terms of privacy, like a new field? Or customizable fields in the expense form?

authors: Betree shannondwray


text:
Added status 202 Accepted as an admissible response status

Added status 202 Accepted as an admissible value in response to Simple Update request send from plugin.

+1

Wrong target branch - please choose main as a target.

authors: MaciejMis ehaligow


text:
Update mixed_sp_wrr_traffic_test.go

Leaf-ref and interface-ref validation added for cisco

Pull Request Test Coverage Report for Build 5399850488

0 of 0   changed or added relevant lines in 0 files are covered.
No unchanged relevant lines lost coverage.
Overall coverage remained the same at 47.655%

Totals

Change from base Build 5396272046:
0.0%

Covered Lines:
1341

Relevant Lines:
2814

💛  - Coveralls

repo: openconfig/featureprofiles


text:
lables: use labels instead of annotation in the description of labels

Signed-off-by: Lei Jitang leijitang@huawei.com

14118d2f looks good to me.  Ping @vbatts (since it's updating your
#371).

LGTM

LGTM

authors: coolljt0725 jonboulle vbatts wking

repo: opencontainers/image-spec


text:
Do not silently omit Neo4j entities with incompatible property types

If a node/rel owns a property with an incompatible type, we currently skip the whole entity silently. Instead, we should log warnings and document that behaviour (probably within the DS itself?).

solved in #546

repo: opencypher/cypher-for-apache-spark


text:
Sync release to main branches for 2.16

Description

How Has This Been Tested?

Merge criteria:

[ ] The commits are squashed in a cohesive manner and have meaningful messages.
[ ] Testing instructions have been added in the PR body (for PRs involving changes that are not immediately obvious).
[ ] The developer has manually tested the changes and verified that the changes work

/lgtm

/pj-rehearse auto-ack

authors: rpancham vaibhavjainwiz

repo: opendatahub-io/caikit-tgis-serving


text:
Retrigger build

FILL IN THE PR DESCRIPTION HERE
FIX #xxxx (link existing issues this PR will resolve)
BEFORE SUBMITTING, PLEASE READ THE CHECKLIST BELOW AND FILL IN THE DESCRIPTION ABOVE

 PR Checklist (Click to Expand)
Thank you for your contribution to vLLM! Before submitting the pull request, please ensure the PR meets the following criteria. This helps vLLM maintain the code quality and improve the efficiency of the review process.
PR Title and Classification
Only specific types of PRs will be reviewed. The PR title is prefixed appropriately to indicate the type of change. Please use one of the following:

[Bugfix] for bug fixes.
[CI/Build] for build or continuous integration improvements.
[Doc] for documentation fixes and improvements.
[Model] for adding a new model or improving an existing model. Model name should appear in the title.
[Frontend] For changes on the vLLM frontend (e.g., OpenAI API server, LLM class, etc.)
[Kernel] for changes affecting CUDA kernels or other compute kernels.
[Core] for changes in the core vLLM logic (e.g., LLMEngine, AsyncLLMEngine, Scheduler, etc.)
[Hardware][Vendor] for hardware-specific changes. Vendor name should appear in the prefix (e.g., [Hardware][AMD]).
[Misc] for PRs that do not fit the above categories. Please use this sparingly.

Note: If the PR spans more than one category, please include all relevant prefixes.
Code Quality
The PR need to meet the following code quality standards:

We adhere to Google Python style guide and Google C++ style guide.
Pass all linter checks. Please use format.sh to format your code.
The code need to be well-documented to ensure future contributors can easily understand the code.
Include sufficient tests to ensure the project to stay correct and robust. This includes both unit tests and integration tests.
Please add documentation to docs/source/ if the PR modifies the user-facing behaviors of vLLM. It helps vLLM user understand and utilize the new features or changes.

Adding or changing kernels
Each custom kernel needs a schema and one or more implementations to be registered with PyTorch.

Make sure custom ops are registered following PyTorch guidelines: Custom C++ and CUDA Operators and The Custom Operators Manual
Custom operations that return Tensors require meta-functions. Meta-functions should be implemented and registered in python so that dynamic dims can be handled automatically. See above documents for a description of meta-functions.
Use torch.libary.opcheck() to test the function registration and meta-function for any registered ops.  See tests/kernels for examples.
When changing the C++ signature of an existing op, the schema must be updated to reflect the changes.
If a new custom type is needed, see the following document: Custom Class Support in PT2.

Notes for Large Changes
Please keep the changes as concise as possible. For major architectural changes (>500 LOC excluding kernel/data/config/test), we would expect a GitHub issue (RFC) discussing the technical design and justification. Otherwise, we will tag it with rfc-required and might not go through the PR.
What to Expect for the Reviews
The goal of the vLLM team is to be a transparent reviewing machine. We would like to make the review process transparent and efficient and make sure no contributor feel confused or frustrated. However, the vLLM team is small, so we need to prioritize some PRs over others. Here is what you can expect from the review process:

 After the PR is submitted, the PR will be assigned to a reviewer. Every reviewer will pick up the PRs based on their expertise and availability.
 After the PR is assigned, the reviewer will provide status update every 2-3 days. If the PR is not reviewed within 7 days, please feel free to ping the reviewer or the vLLM team.
 After the review, the reviewer will put an  action-required label on the PR if there are changes required. The contributor should address the comments and ping the reviewer to re-review the PR.
 Please respond to all comments within a reasonable time frame. If a comment isn't clear or you disagree with a suggestion, feel free to ask for clarification or discuss the suggestion.

Thank You
 Finally, thank you for taking the time to read these guidelines and for your interest in contributing to vLLM. Your contributions make vLLM a great tool for everyone!

/lgtm
/ok-to-test
/pj-rehearse auto-ack

/cherry-pick release

repo: opendatahub-io/vllm


text:
Applicazione android

Salve,
Ho creato un'applicazione android per la visualizzazione dei dati su cellulare.

@francescovallone fa piacere quello che stai facendo.
Perché non aggiungi nel repo del branch master, nel README, un paragrafo dedicato a questa app, con qualche parola di descrizione e uno (o più) screenshot?

Provvedo subito!

authors: aborruso francescovallone


text:
Correzione typo nome OpenStreetMap

Piccola imprecisione nel nome del progetto OpenStreetMap

Grazie

authors: LorenzoStucchi aborruso


text:
Fixing off by one in gdb backtrace

Following outcome of static code analysis, fixing an off by one error, where string null termination character was written outside of string's buffer.

Looks good but you need to add the signed-off-by to your commit.

Done, git sanity checks have passed.

repo: opendcdiag/opendcdiag


text:
Browser display broken

The page looks really broken from me on Mac Chrome/Safari ...

Should be fixed in #18

In the last merge the divs for the sonarqube logos haven't been closed correctly.

After merge the page isn't broken anymore, but the sonatype logo is stretched. This will be tarcked in a new issue

authors: michaelsauter tjaeschke


text:
polish(zhangpai): polish slime_volley league training

Description

Related Issue
#90
TODO
Check List

[ ] merge the latest version source branch/repo, and resolve all the conflicts
[ ] pass style check
[ ] pass all the tests

Please plot a curve of TrueSkill score vs training time.

What is the latest main agent's mean reward when playing with this AI?

@PaParaZz1 Why this Pull Request is closed?

repo: opendilab/DI-engine


text:
audit not working for e.g. delete index or query index ... only for failed login

Hi,
this is one question from opendistro forum (user: Xyrion):
I have a scenario where I need to record if an admin deletes an index or a record from an index. Is this possible? I enabled the opendistro audit and tested to delete an index but it didn’t show up in my esaudit index. I can however see data flowing in to the esaudit in relation to Transport SSL, meaning the audit functionality is working.
I setup audit with the following config:
opendistro_security.audit.type: internal_elasticsearch
opendistro_security.audit.config.index: “'esaudit-'YYYY.MM.dd”
opendistro_security.audit.ignore_users: NONE
Is there additional config that I can add to track what the users does once they have authenticated.
Additional info: I used a simple curl with the -u to delete the index.
my case (user: mato69) is similar, we want (if it's possible) to have records/log for access, query, delete index and so on ... this is our elasticsearch.yml:
...
opendistro_security.audit.enable_transport: true
opendistro_security.audit.resolve_bulk_requests: true
opendistro_security.audit.enable_rest: true
#opendistro_security.audit.enable_request_details: true
opendistro_security.audit.log_request_body: true
opendistro_security.audit.resolve_indices: true
...
opendistro_security.audit.enable_request_details is not working so it's #

for others with my problem, finally i went with  https://www.elastic.co/blog/monitoring-the-search-queries ssl from client browser to kibana and then clear http from kibana to elasticsearch (same server). Packetbeat, max message 20k.

@mato69 Currently audit logging of document deletion in an index is supported.
Please specify the index that you want to monitor for doc writes using
opendistro_security.compliance.history.write.watched_indices: ["name-of-index"]

There is new category "INDEX_EVENT" logged on transport layer and all "indices:admin/*" events will be logged including "indices:admin/delete". Please check v1.9.0.1 release

repo: opendistro-for-elasticsearch/security


text:
False Positive with Windows Defender

This is a Windows Defender issue probably, so it would be best to tell them, also since you posted this it has probably been corrected in their signatures.

authors: HauptJ jmfgdev

repo: opendns/dnscrypt-win-client

license: isc


text:
feat(control plane): allow images to be built

Provide the ability to build container images for the various control
plane components.
Before performing a nix-build, ensure you are in the ../Mayastor
directory.
e.g.
To build a specific control plane service image such as the node
service:
nix-build -A services.node-image
To build a development image, add the "-dev" suffix:
nix-build -A services.node-image-dev
To build all service images:
nix-build -A services
e.g.
To build a specific operator such as the node operator:
nix-build -A operators.node-image
To build a development image, add the "-dev" suffix:
nix-build -A operators.node-image-dev
To build all operator images:
nix-build -A operators

Closing this PR as additional changes are required.

Closing this PR as additional changes are required.

repo: openebs/Mayastor


text:
Ensure jiva controllers spin up on new nodes on priority if its node crashes

maya api service should apply appropriate policies (K8s based) which will ensure jiva controllers to be spawned ASAP on available node (belonging to the cluster) if its node crashes.
Why ?

K8s will probably have a hard time evacuating all the PODs in the just crashed node
Jiva being a persistent storage container should be given priority among all others.
This flip in the uptime of jiva controller should not break its storage / protocol connection with the apps.

This seems to be opposite of node affinity feature that is required for replicas.
Hence referring issue https://github.com/openebs/mayaserver/issues/91

Details

Launching kube-controller-manager uses TaintBasedEvictions:

  - command:
    - kube-controller-manager
    - --use-service-account-credentials=true
    - --controllers=*,bootstrapsigner,tokencleaner
    - --kubeconfig=/etc/kubernetes/controller-manager.conf
    - --root-ca-file=/etc/kubernetes/pki/ca.crt
    - --cluster-signing-key-file=/etc/kubernetes/pki/ca.key
    - --leader-elect=true
    - --service-account-private-key-file=/etc/kubernetes/pki/sa.key
    - --cluster-signing-cert-file=/etc/kubernetes/pki/ca.crt
    - --address=127.0.0.1
    - --feature-gates=TaintBasedEvictions=true

Tolerations within the controller specs:

"tolerations": [
            {
                "effect": "NoExecute",
                "key": "node.alpha.kubernetes.io/notReady",
                "operator": "Exists",
                "tolerationSeconds": 0
            },
            {
                "effect": "NoExecute",
                "key": "node.alpha.kubernetes.io/unreachable",
                "operator": "Exists",
                "tolerationSeconds": 0
            }
        ],

Observations

vagrant halt kubeminion-03

ubuntu@kubemaster-01:/vagrant$ date
Tue Aug  8 05:45:10 UTC 2017

ubuntu@kubemaster-01:/vagrant$ kubectl get pod
NAME                                   READY     STATUS    RESTARTS   AGE
maya-apiserver-3516355633-2sqlt        1/1       Running   0          44m
my-2-jiva-vsm-ctrl-858778907-3rp28     1/1       Running   0          8m
my-2-jiva-vsm-rep-1743760321-f9swv     1/1       Running   0          8m
my-2-jiva-vsm-rep-1743760321-stmdt     1/1       Running   0          8m
openebs-provisioner-3862123968-cx1vs   1/1       Running   0          48m

ubuntu@kubemaster-01:/vagrant$ date
Tue Aug  8 05:46:07 UTC 2017

ubuntu@kubemaster-01:/vagrant$ kubectl get nodes
NAME            STATUS    AGE       VERSION
kubemaster-01   Ready     4d        v1.7.0
kubeminion-01   Ready     4d        v1.7.0
kubeminion-02   Ready     4d        v1.7.0
kubeminion-03   Ready     4d        v1.7.0

ubuntu@kubemaster-01:/vagrant$ date
Tue Aug  8 05:46:55 UTC 2017

ubuntu@kubemaster-01:/vagrant$ kubectl get pod
NAME                                   READY     STATUS              RESTARTS   AGE
maya-apiserver-3516355633-2sqlt        1/1       Running             0          46m
my-2-jiva-vsm-ctrl-858778907-3rp28     1/1       Terminating         0          10m
my-2-jiva-vsm-ctrl-858778907-fxj3c     0/1       ContainerCreating   0          1s
my-2-jiva-vsm-rep-1743760321-f9swv     1/1       Running             0          10m
my-2-jiva-vsm-rep-1743760321-stmdt     1/1       Running             0          10m
openebs-provisioner-3862123968-cx1vs   1/1       Running             0          49m

ubuntu@kubemaster-01:/vagrant$ date
Tue Aug  8 05:47:02 UTC 2017

ubuntu@kubemaster-01:/vagrant$ kubectl get pod
NAME                                   READY     STATUS        RESTARTS   AGE
maya-apiserver-3516355633-2sqlt        1/1       Running       0          46m
my-2-jiva-vsm-ctrl-858778907-3rp28     1/1       Terminating   0          10m
my-2-jiva-vsm-ctrl-858778907-fxj3c     1/1       Running       0          7s
my-2-jiva-vsm-rep-1743760321-f9swv     1/1       Running       0          10m
my-2-jiva-vsm-rep-1743760321-stmdt     1/1       Running       0          10m
openebs-provisioner-3862123968-cx1vs   1/1       Running       0          50m

vagrant up kubeminion-03

ubuntu@kubemaster-01:/vagrant$ date
Tue Aug  8 05:57:21 UTC 2017

ubuntu@kubemaster-01:/vagrant$ kubectl get pod
NAME                                   READY     STATUS    RESTARTS   AGE
maya-apiserver-3516355633-2sqlt        1/1       Running   0          56m
my-2-jiva-vsm-ctrl-858778907-fxj3c     1/1       Running   0          10m
my-2-jiva-vsm-rep-1743760321-f9swv     0/1       Error     0          20m
my-2-jiva-vsm-rep-1743760321-stmdt     1/1       Running   0          20m
openebs-provisioner-3862123968-cx1vs   1/1       Running   0          1h

ubuntu@kubemaster-01:/vagrant$ kubectl get pod
NAME                                   READY     STATUS    RESTARTS   AGE
maya-apiserver-3516355633-2sqlt        1/1       Running   0          57m
my-2-jiva-vsm-ctrl-858778907-fxj3c     1/1       Running   0          10m
my-2-jiva-vsm-rep-1743760321-f9swv     1/1       Running   1          20m
my-2-jiva-vsm-rep-1743760321-stmdt     1/1       Running   0          20m
openebs-provisioner-3862123968-cx1vs   1/1       Running   0          1h

repo: openebs/mayaserver


text:
[BD-46] feat: development Truncate component

Description
The base requirements for a standalone component would be as follows:

Customize the number of lines of text that should be preserved.
Customize the ellipsis, but it should default to … (accepting string or another component)
Provide an option to trim unnecessary whitespace.. That is, any extra spaces between a truncated string and the `…, e.g. "courses ..." would become "courses..."
Standalone component page on the Paragon documentation site with example usage.
Added new onTruncate props.

Deploy Preview
Truncate component
Merge Checklist

[x] If your update includes visual changes, have they been reviewed by a designer? Send them a link to the Netlify deploy preview, if applicable.
[x] Does your change adhere to the documented style conventions?
[x] Do any prop types have missing descriptions in the Props API tables in the documentation site (check deploy preview)?
[x] Were your changes tested using all available themes (see theme switcher in the header of the deploy preview, under the "Settings" icon)?
[x] Were your changes tested in the example app?
[x] Is there adequate test coverage for your changes?
[x] Consider whether this change needs to reviewed/QA'ed for accessibility (a11y). If so, please add wittjeff and adamstankiewicz as reviewers on this PR.

Post-merge Checklist

[x] Verify your changes were released to NPM at the expected version.
[x] If you'd like, share your contribution in #show-and-tell.
[x] 🎉 🙌 Celebrate! Thanks for your contribution.

Thanks for the pull request, @PKulkoRaccoonGang!
When this pull request is ready, tag your edX technical lead.

I've noticed the occasional odd behavior with Truncate (e.g., it occasionally shows 2.5 lines with the ellipsis half way through a line), though I haven't  been able to really identify an exact issue. From the sync earlier today, @monteri mentioned potentially using ResizeObserver here which might improve the truncate behavior.
Likewise, we discussed another prop (onTruncate) for this component that would be great for consumers to know when their content is truncated (e.g., to render a tooltip only when text is truncated). We can treat that as a separate task (let's file a new Github issue in this case), or build it into this PR; I'll leave that decision up to you!

@PKulkoRaccoonGang 🎉 Your pull request was merged!  Please take a moment  to answer a two question survey so we can improve your experience in the future.

:tada: This PR is included in version 20.10.0 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

authors: PKulkoRaccoonGang adamstankiewicz edx-semantic-release openedx-webhooks

repo: openedx/paragon


text:
Paragon vulnerablities resolution

Description

Updated gatsby to latest version & packages in package-lock.json to resolve vulnerabilities

Deploy Preview
Include a direct link to your changes in this PR's deploy preview here (e.g., a specific component page).
Merge Checklist

[ ] If your update includes visual changes, have they been reviewed by a designer? Send them a link to the Netlify deploy preview, if applicable.
[ ] Does your change adhere to the documented style conventions?
[ ] Do any prop types have missing descriptions in the Props API tables in the documentation site (check deploy preview)?
[ ] Were your changes tested using all available themes (see theme switcher in the header of the deploy preview, under the "Settings" icon)?
[ ] Were your changes tested in the example app?
[ ] Is there adequate test coverage for your changes?
[ ] Consider whether this change needs to reviewed/QA'ed for accessibility (a11y). If so, please add wittjeff and adamstankiewicz as reviewers on this PR.

Post-merge Checklist

[ ] Verify your changes were released to NPM at the expected version.
[ ] If you'd like, share your contribution in #show-and-tell.
[ ] 🎉 🙌 Celebrate! Thanks for your contribution.

@BilalQamar95 When you get a chance, I have a couple requests for this PR:

Should we split out the @edx/frontend-build upgrade and subsequent ESLint changes as its own PR? That would leave this PR only for upgrading the Gatsby and package-lock.json modules.
Can we get this back up to date with master?

@BilalQamar95 When you get a chance, I have a couple requests for this PR:

~Can we split out the @edx/frontend-build upgrade and subsequent ESLint changes as its own PR?~ That would leave this PR only for upgrading the Gatsby and package-lock.json modules.
Can we get this back up to date with master?

Apologies, it looks like @edx/frontend-build is already at v12.3.0 in this repo. The Gatsby ecosystem upgrade is definitely still relevant, though (related PR).

This seems like it's still relevant.  @BilalQamar95, do you mind resolving conflicts?  @adamstankiewicz, once he does, any objections to merging it?

:tada: This PR is included in version 20.40.2 :tada:
The release is available on:

npm package (@latest dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

:tada: This PR is included in version 21.0.0-alpha.31 :tada:
The release is available on:

npm package (@alpha dist-tag)
GitHub release

Your semantic-release bot :package::rocket:

authors: BilalQamar95 adamstankiewicz arbrandes edx-semantic-release


text:
Attachment link error when uploading a SCORM package as a regular ZIP file

When a valid SCORM package is added as a regular ZIP file, if you unzip and select a file to display in the item summary page, the link to the file will consist of "/_upload/.........." in the URL which returns 404.

Still a problem

repo: openequella/openEQUELLA


text:
#1317 upgrade Jackson to 2.10.2

Checklist

[x] the contributor license agreement is signed
[x] commit message follows commit guidelines

Description of change
#1317
Upgrade the Jackson deps to 2.10.2 (which also matches the Jackson version in the admin console).
Locally, I didn't see the sbt deduplication issues mentioned in the ticket.  We'll see how the CI builds turn out.

Interesting - I can build installerZip locally, but Travis fails with the deduplication issue.  I need to explore a bit more.

Primary issue - jakarta.xml.bind-api-2.3.2.jar was colliding with jaxb-api-2.2.2.jar on classes in javax.xml.bind.*
Jakarta is coming from the upgraded Jackson deps, and jaxb-api-2.2.2 comes in via org.apache.cxf:cxf-bundle:2.7.6 and com.microsoft.sqlserver:mssql-jdbc:6.1.0.jre8
It was already excluded from cxf, and I ended up excluding it from mssql-jdbc since the Jakarta was a minor version bump.

Need to do a final review of the change log and then I'll merge it in.


text:
Update actions cache handling

Description
Simplify cache setup of Go dependencies as well as normalize cache action version.
References

Review Checklist

[x] I have added documentation for new/changed functionality in this PR or in openfga.dev
[x] The correct base branch is being used, if not main

 Thank you for your submission! We really appreciate it. Like many open source projects, we ask that you sign our Contributor License Agreement before we can accept your contribution.You have signed the CLA already but the status is still pending? Let us recheck it.

repo: openfga/openfga


text:
Define PLATFORM and PLATFORM_NUMBER based on the minimum Android SDK Version.

This PR updates PLATFORM and adds PLATFORM_NUMBER to match with the project's minimum Android SDK version, moving away from the previous hardcoding of android-21.

@player-03 May i get a review on this pr?

Does this break any existing workflow?

Does this break any existing workflow?

I don't think it would break anything. I've tested this on a project and it works just fine.

Does this break any existing workflow?

I don't think it would break anything. I've tested this on a project and it works just fine.

Wont developers need to include these in their project xml now?

Does this break any existing workflow?

I don't think it would break anything. I've tested this on a project and it works just fine.

Wont developers need to include these in their project xml now?

Noup, using project.config.getInt("android.minimum-sdk-version", 21); makes it so 21 is the default value if there no version found within project.xml

Sounds good. Close this and PR to the correct 8.3 branch though.

I changed the base branch to 8.3.0-Dev.

Uh, i think i broke something, I'll close this and change the branch

repo: openfl/lime


text:
[ru] Some lists have no space after commas.

https://ru.openfoodfacts.org/product/40084701/kinder-chocolate-ferrero

This issue has been solved in PR #468.

repo: openfoodfacts/openfoodfacts-androidapp


text:
Fixed grey food scores displayed for cosmetics

Description
Added a if block to check the build flavor. If the build flavor is  "off" then only the food scores are visible.
Related issues
Fixes #3741
Related PRs
None
Screenshots

@VaiTon Changes done accordingly !

@VaiTon Changes done accordingly !


text:
Check lookup tables for values before ChemicalDomains

Fixes #144
Changes made in this Pull Request:

PR Checklist

[ ] Tests?
[ ] Docs?
[ ] CHANGELOG updated?
[ ] Issue raised/referenced?

Codecov Report
All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 63.66%. Comparing base (1d7e4ff) to head (92d3ccf).

:exclamation:  There is a different number of reports uploaded between BASE (1d7e4ff) and HEAD (92d3ccf). Click for more details.
HEAD has 51 uploads less than BASE

Flag
BASE (1d7e4ff)
HEAD (92d3ccf)

52
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Additional details and impacted files

authors: codecov-commenter lilyminium

repo: openforcefield/openff-nagl


text:
Improve compatibility with non-Psi4 engines

Description
The current logic makes it difficult to use QC packages supported by QCEngine besides Psi4. This updates the logic to not assume that the program argument is in the settings dictionary.
Todos
Notable points that this PR has either accomplished or will accomplish.

[ ] TODO 1

Questions

[ ] Question1

Status

[ ] Ready to go

The docs builds were broken because an old QCPortal was being brought in, somehow. 6553fc4183b21ac63bdb2af733eefa7a33587cfd should fix that, but there might be other issues.

The change in 7e4d0911fb1dbc0a065bf4759821c0dd3e4a990f is a fairly naive way of getting tests to pass, but if I understand the change correctly it's in line with the intended changes; I think that previously the supported methods were implied by the keys in the settings and anything not recognized produced an error. The point of this change is to allow unrecognized methods through - presumably letting some errors pass through if users are using methods outside of the scope of current QCSubmit usage.
(I'm maybe 80% sure I'm using the right jargon here - method/program/settings/etc. - please correct me if I'm mistaken!)

The point of this change is to allow unrecognized methods through

Almost but its programs, the test was checking if an error was raised if an unsupported program of QCEngine was supplied. It should have probably been checking with qcengine if the program is supported but this will also limit the programs to only those supported in the main version and not ones supplied via plugins, but that might be the best we can do for now.

authors: jthorton mattwthompson

repo: openforcefield/openff-qcsubmit


text:
Fix conda install instructions

Moved icoscp to pip section of environment.yaml and corrected msgpack package name to msgpack-python.
Need to do some additional checks to make sure this works correctly so a draft for now.

Codecov Report

Merging #495 (50c1bd5) into devel (3d249ed) will increase coverage by 0.79%.
The diff coverage is 89.38%.

@@            Coverage Diff             @@
##            devel     #495      +/-   ##
==========================================
+ Coverage   77.49%   78.28%   +0.79%
==========================================
  Files         168      170       +2
  Lines       12049    12494     +445
==========================================
+ Hits         9337     9781     +444
- Misses       2712     2713       +1

Impacted Files
Coverage Δ

openghg/analyse/_scenario.py
76.79% <ø> (ø)

openghg/objectstore/__init__.py
71.42% <ø> (ø)

openghg/retrieve/__init__.py
100.00% <ø> (ø)

openghg/standardise/_standardise.py
57.30% <ø> (ø)

openghg/transform/emissions/_edgar.py
78.79% <ø> (ø)

openghg/tutorial/__init__.py
100.00% <ø> (ø)

tests/conftest.py
71.87% <ø> (+2.43%)
:arrow_up:

tests/db_integrity/test_data_updates.py
97.15% <ø> (ø)

tests/helpers/__init__.py
100.00% <ø> (ø)

openghg/tutorial/_tutorial.py
33.57% <24.32%> (+0.24%)
:arrow_up:

... and 32 more

Help us with your feedback. Take ten seconds to tell us how you rate us. Have a feature suggestion? Share it here.

authors: codecov-commenter gareth-j

repo: openghg/openghg


text:
Add code to choose log normal prior with given mean and stdev

The mu and sigma parameters for pymc's log normal distribution are the not the mean and standard deviation of the log normal. If X is a log normal random variable then log X is a normal random variable, and pymc's mu and sigma are the mean and standard deviation of log X.
There is a fairly simple formula that produces mu and sigma to get a log normal with a given mean and standard deviation. It would be useful to have this incorporated into our code.

Closed by PR #109